Outside Box and Contactless Palm Vein Recognition Based on a Wavelet Denoising ResNet
Palm vein recognition is a high-security biometric. Outside the NIR capture box and contactless palm vein recognition are more popular but challenging. The users feel comfortable outside the NIR capture box but face more optical blurring brought by visible light. Contactless capture gestures solve t...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9447736/ |
| _version_ | 1818898134283059200 |
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| author | Wei Wu Qiang Wang Siquan Yu Qiong Luo Sen Lin Zhi Han Yandong Tang |
| author_facet | Wei Wu Qiang Wang Siquan Yu Qiong Luo Sen Lin Zhi Han Yandong Tang |
| author_sort | Wei Wu |
| collection | DOAJ |
| description | Palm vein recognition is a high-security biometric. Outside the NIR capture box and contactless palm vein recognition are more popular but challenging. The users feel comfortable outside the NIR capture box but face more optical blurring brought by visible light. Contactless capture gestures solve the hygienic problem but face the image rotation, position translation, and scale transformation which makes classification difficult especially in large-scale databases. To address these problems, we develop a wavelet denoising ResNet, which consists of two models: the wavelet denoising (WD) model and the squeeze-and-excitation ResNet18 (SER) model. The WD model focuses on removing noise from skin scattering and optical blurring from palm vein images. The WD model enhances the low-frequency feature into a deep learning feature by residual learning technology. This strategy increases the weight of an effective handcrafted feature in the deep learning network. The SER model overcomes rotation, position translation, and scale transformation by selectively emphasizing classification features and weakening less useful features. To train and verify the network, an inside box palm vein image database and an outside box palm vein image database are set up. The Tongji contactless palm vein image database was also employed in the experiments. The validity and superiority of our network are verified in a series of experiments. |
| first_indexed | 2024-12-19T19:27:14Z |
| format | Article |
| id | doaj.art-2bba3bbc084e4977bf0e48640db7d8c5 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T19:27:14Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-2bba3bbc084e4977bf0e48640db7d8c52022-12-21T20:08:44ZengIEEEIEEE Access2169-35362021-01-019824718248410.1109/ACCESS.2021.30868119447736Outside Box and Contactless Palm Vein Recognition Based on a Wavelet Denoising ResNetWei Wu0https://orcid.org/0000-0001-9382-4946Qiang Wang1https://orcid.org/0000-0002-2018-1764Siquan Yu2https://orcid.org/0000-0003-2513-9175Qiong Luo3https://orcid.org/0000-0003-0015-1151Sen Lin4https://orcid.org/0000-0003-2051-3500Zhi Han5https://orcid.org/0000-0002-8039-6679Yandong Tang6https://orcid.org/0000-0003-3805-7654Information Engineering Department, Shenyang University, Shenyang, ChinaInformation Engineering Department, Shenyang University, Shenyang, ChinaState Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, ChinaState Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, ChinaSchool of Automation and Electrical Engineering, Shenyang Ligong University, Shenyang, ChinaState Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, ChinaState Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, ChinaPalm vein recognition is a high-security biometric. Outside the NIR capture box and contactless palm vein recognition are more popular but challenging. The users feel comfortable outside the NIR capture box but face more optical blurring brought by visible light. Contactless capture gestures solve the hygienic problem but face the image rotation, position translation, and scale transformation which makes classification difficult especially in large-scale databases. To address these problems, we develop a wavelet denoising ResNet, which consists of two models: the wavelet denoising (WD) model and the squeeze-and-excitation ResNet18 (SER) model. The WD model focuses on removing noise from skin scattering and optical blurring from palm vein images. The WD model enhances the low-frequency feature into a deep learning feature by residual learning technology. This strategy increases the weight of an effective handcrafted feature in the deep learning network. The SER model overcomes rotation, position translation, and scale transformation by selectively emphasizing classification features and weakening less useful features. To train and verify the network, an inside box palm vein image database and an outside box palm vein image database are set up. The Tongji contactless palm vein image database was also employed in the experiments. The validity and superiority of our network are verified in a series of experiments.https://ieeexplore.ieee.org/document/9447736/Deep learningbiometricspalm vein recognitionResnetwavelet decompositiondenoise |
| spellingShingle | Wei Wu Qiang Wang Siquan Yu Qiong Luo Sen Lin Zhi Han Yandong Tang Outside Box and Contactless Palm Vein Recognition Based on a Wavelet Denoising ResNet IEEE Access Deep learning biometrics palm vein recognition Resnet wavelet decomposition denoise |
| title | Outside Box and Contactless Palm Vein Recognition Based on a Wavelet Denoising ResNet |
| title_full | Outside Box and Contactless Palm Vein Recognition Based on a Wavelet Denoising ResNet |
| title_fullStr | Outside Box and Contactless Palm Vein Recognition Based on a Wavelet Denoising ResNet |
| title_full_unstemmed | Outside Box and Contactless Palm Vein Recognition Based on a Wavelet Denoising ResNet |
| title_short | Outside Box and Contactless Palm Vein Recognition Based on a Wavelet Denoising ResNet |
| title_sort | outside box and contactless palm vein recognition based on a wavelet denoising resnet |
| topic | Deep learning biometrics palm vein recognition Resnet wavelet decomposition denoise |
| url | https://ieeexplore.ieee.org/document/9447736/ |
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